85
Views
0
CrossRef citations to date
0
Altmetric
Research Article

A numerical study on the behaviour of foundations resting on fibre reinforced soils using an innovative enhanced soil-fibre finite element

, &
Pages 613-629 | Received 23 Jan 2020, Accepted 18 Sep 2020, Published online: 14 Oct 2020
 

ABSTRACT

A numerical study has been conducted to investigate the behaviour of footings (i.e. the settlement and the bearing capacity) resting on fibre reinforced soils. An innovative Enhanced Soil-Fibre (ESF) Finite Element has been introduced and implemented in order to more efficiently analyse the behaviour of such footings. The ESF element is a 16-noded finite element with a central region specified for the fibre geometrical and mechanical properties. This element can be effectively used in place of a rather fine mesh to fully model the arbitrarily distributed fibres in a soil body. Therefore, the computational efforts become considerably less in comparison with conventional finite element modelling. A series of design charts have been presented to avail direct application of the results for practical purposes. The design charts contain the settlement reduction factor or the bearing capacity factor relating the behaviour of footings on reinforced soils to those on unreinforced soils. Design charts are developed for a wide range of mechanical properties common in practical cases.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 203.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.